Install detectron2

Train on a custom COCO dataset

Register the V-COCO dataset to detectron2.

To verify the data loading is correct, let's visualize the annotations of randomly selected samples in the training set:

Now, let's fine-tune a coco-pretrained R50-FPN Mask R-CNN model on the fruits_nuts dataset. It takes ~6 minutes to train 300 iterations on Colab's K80 GPU.

Now, we perform inference with the trained model on the fruits_nuts dataset. First, let's create a predictor using the model we just trained:

Run Eval Metrics for 0.5

Then, we randomly select several samples to visualize the prediction results.

Run Eval Metrics for 0.4

Train on Faster RCNN Model

COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml

Train on Retinent Model 50

Run Action on Images